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Herd Behavior And Nonfundamental Asset Price Fluctuations In Financial Markets

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  • BISCHI, GIAN-ITALO
  • GALLEGATI, MAURO
  • GARDINI, LAURA
  • LEOMBRUNI, ROBERTO
  • PALESTRINI, ANTONIO
Abstract
In this paper we investigate the effects of herding on asset price dynamics during continuous trading. We focus on the role of interaction among traders, and we investigate the dynamics emerging when we allow for a tendency to mimic the actions of other investors, that is, to engage in herd behavior. The model, built as a mean field in a binary setting (buy/sell decisions of a risky asset), is expressed by a three-dimensional discrete dynamical system describing the evolution of the asset price, its expected price, and its excess demand. We show that such dynamical system can be reduced to a unidirectionally coupled system. In line with the rational herd behavior literature [Bikhchandani, S., Sharma, S. (2000), Herd Behavior in Financial Markets: A Review. Working paper, IMF, WP/00/48], situations of multistability are observed, characterized by strong path dependence; that is, the dynamics of the system are strongly influenced by historical accidents. We describe the different kinds of dynamic behavior observed, and we characterize the bifurcations that mark the transitions between qualitatively different time evolutions. Some situations give rise to high sensitivity with respect to small changes of the parameters and/or initial conditions, including the possibility of invest or reject cascades (i.e., sudden uncontrolled increases or crashes of the prices).

Suggested Citation

  • Bischi, Gian-Italo & Gallegati, Mauro & Gardini, Laura & Leombruni, Roberto & Palestrini, Antonio, 2006. "Herd Behavior And Nonfundamental Asset Price Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 10(4), pages 502-528, September.
    • Handle: RePEc:cup:macdyn:v:10:y:2006:i:04:p:502-528_05
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    Cited by:

    1. Mine Caglar, 2011. "Stock Price Processes with Infinite Source Poisson Agents," Papers 1106.6300, arXiv.org.
    2. Ilaria Foroni & Anna Agliari, 2008. "Complex Price Dynamics in a Financial Market with Imitation," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 21-36, September.
    3. Giovanni Campisi & Silvia Muzzioli & Fabio Tramontana, 2021. "Uncertainty about fundamental, pessimistic and overconfident traders: a piecewise-linear maps approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 707-726, December.
    4. Roy Cerqueti & Giulia Rotundo, 2015. "A review of aggregation techniques for agent-based models: understanding the presence of long-term memory," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1693-1717, July.
    5. Harras, Georges & Sornette, Didier, 2011. "How to grow a bubble: A model of myopic adapting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 80(1), pages 137-152.
    6. Gallegati, Mauro & Palestrini, Antonio & Rosser, J. Barkley, 2011. "The Period Of Financial Distress In Speculative Markets: Interacting Heterogeneous Agents And Financial Constraints," Macroeconomic Dynamics, Cambridge University Press, vol. 15(1), pages 60-79, February.
    7. Fabio Tramontana, 2013. "The role of cognitively biased imitators in a small scale agent-based financial market," DEM Working Papers Series 029, University of Pavia, Department of Economics and Management.
    8. Sarah Mignot & Fabio Tramontana & Frank Westerhoff, 2021. "Speculative asset price dynamics and wealth taxes," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 641-667, December.
    9. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2018. "Market entry waves and volatility outbursts in stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 19-37.
    10. Roberto Dieci & Xue-Zhong He, 2021. "Cross-section instability in financial markets: impatience, extrapolation, and switching," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 727-754, December.
    11. Emilio Barucci & Marco Tolotti, 2009. "The dynamics of social interaction with agents’ heterogeneity," Working Papers 189, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    12. Damian Smug & Peter Ashwin & Didier Sornette, 2018. "Predicting financial market crashes using ghost singularities," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-20, March.
    13. Bowden, Mark P., 2012. "Information contagion within small worlds and changes in kurtosis and volatility in financial prices," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 553-566.
    14. Giovanni Campisi & Silvia Muzzioli & Fabio Tramontana, 2021. "Uncertainty about fundamental and pessimistic traders: a piecewise-linear maps approach," Department of Economics 0186, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    15. Ehsan Ahmed & J. Barkley Rosser Jr. & Jamshed Y. Uppal, 2010. "Emerging Markets and Stock Market Bubbles: Nonlinear Speculation?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(4), pages 23-40, January.

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